Showing papers on "Traffic simulation published in 2006"

The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

Abstract: Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow simulation model MIXIC that was specially designed to study the impact of intelligent vehicles on traffic flow. The authors study the impacts of CACC for a highway-merging scenario from four to three lanes. The results show an improvement of traffic-flow stability and a slight increase in traffic-flow efficiency compared with the merging scenario without equipped vehicles

Evaluation of Variable Speed Limits to Improve Traffic Safety

Abstract: This paper examines automated control strategies of variable speed limits that aim at reducing crash potential on instrumented freeways. A real-time crash prediction model was developed to estimate crash potential based on short-term variation of traffic flow characteristics. A microscopic traffic simulation model was used to realistically simulate changes in traffic conditions as an effect of variable speed limits and combined with the crash prediction model for the evaluation of control logics. Within this integrated evaluation framework, the study investigated the effect of strategy control factors on the crash potential reduction and total travel time. The study results indicated that variable speed limits could reduce crash potential by 5–17%, by temporarily reducing speed limits during risky traffic conditions when crash potential exceeded the pre-specified threshold.

The Open Source Traffic Simulation Package SUMO

Abstract: Since the year 2000, the Institute of Transportation Research (IVF) at the German Aerospace Centre (DLR) is developing a microscopic, traffic simulation package. The complete package is offered as open source to establish the software as a common testbed for algorithms and models from traffic research. Since the year 2003 the IVF also works on a virtual traffic management centre and in conjunction with this on traffic management. Several large-scale projects have been done since this time, most importantly INVENT where modern traffic management methods have been evaluated and the online-simulation and prediction of traffic during the world youth day (Weltjugendtag) 2005 in Cologne/Germany. This publication briefly describes the simulation package together with the projects mentioned above to show how SUMO can be used to simulate largescale traffic scenarios. Additionally, it is pointed out how SUMO may be used as a testbed for automatic management algorithms with minor effort in developing extensions.

A compositional stochastic model for real time freeway traffic simulation

Abstract: Traffic flow on freeways is a non-linear, many-particle phenomenon, with complex interactions between vehicles. This paper presents a stochastic model of freeway traffic at a time scale and of a level of detail suitable for on-line estimation, routing and ramp metering control. The freeway is considered as a network of interconnected components, corresponding to one-way road links consisting of consecutively connected short sections (cells). The compositional model proposed here extends the Daganzo cell transmission model by defining sending and receiving functions explicitly as random variables, and by also specifying the dynamics of the average speed in each cell. Simple stochastic equations describing the macroscopic traffic behavior of each cell, as well as its interaction with neighboring cells are obtained. This will allow the simulation of quite large road networks by composing many links. The model is validated over synthetic data with abrupt changes in the number of lanes and over real traffic data sets collected from a Belgian freeway.

RENAISSANCE – A Unified Macroscopic Model-Based Approach to Real-Time Freeway Network Traffic Surveillance

Abstract: The paper presents a unified macroscopic model-based approach to real-time freeway network traffic surveillance as well as a software tool RENAISSANCE that has been recently developed to implement this approach for field applications. RENAISSANCE is designed on the basis of stochastic macroscopic freeway network traffic flow modeling, extended Kalman filtering, and a number of traffic surveillance algorithms. Fed with a limited amount of real-time traffic measurements, RENAISSANCE enables a number of freeway network traffic surveillance tasks, including traffic state estimation and short-term traffic state prediction, travel time estimation and prediction, queue tail/head/length estimation and prediction, and incident alarm. The traffic state estimation and prediction lay the operating foundation of RENAISSANCE since RENAISSANCE bases the other traffic surveillance tasks on its traffic state estimation or prediction results. The paper first introduces the utilized stochastic macroscopic freeway network traffic flow model and a real-time traffic measurement model, upon which the complete dynamic system model of RENAISSANCE is established with special attention to the handling of some important model parameters. The algorithms for the various traffic surveillance tasks addressed are described along with the functional architecture of the tool. A simulation test was conducted via application of RENAISSANCE to a hypothetical freeway network example with a sparse detector configuration, and the testing results are presented in some detail. Final conclusions and future work are outlined.

Neural Network-Wavelet Microsimulation Model for Delay and Queue Length Estimation at Freeway Work Zones

Abstract: Recently, the writers developed a new mesoscopic-wavelet model for simulating freeway traffic flow patterns and extracting congestion characteristics. As an extension of that research, in this paper, a new neural network-wavelet microsimulation model is presented to track the travel time of each individual vehicle for traffic delay and queue length estimation at work zones. The model incorporates the dynamics of a single vehicle in changing traffic flow conditions. The extracted congestion characteristics obtained from the mesoscopic-wavelet model are used in a Levenberg–Marquardt backpropagation (BP) neural network for classifying the traffic flow as free flow, transitional flow, and congested flow with stationary queue. The neural network model is trained using simulated data and tested using both simulated and real data. The computational model presented is applied to five examples of freeways with two and three lanes and one lane closure with varying entry flow or demand patterns. The new microsimulat...

Bi-level Programming Formulation and Heuristic Solution Approach for Dynamic Traffic Signal Optimization

Abstract: : Although dynamic traffic control and traffic assignment are intimately connected in the framework of Intelligent Transportation Systems (ITS), they have been developed independent of one another by most existing research. Conventional methods of signal timing optimization assume given traffic flow pattern, whereas traffic assignment is performed with the assumption of fixed signal timing. This study develops a bi-level programming formulation and heuristic solution approach (HSA) for dynamic traffic signal optimization in networks with time-dependent demand and stochastic route choice. In the bi-level programming model, the upper level problem represents the decision-making behavior (signal control) of the system manager, while the user travel behavior is represented at the lower level. The HSA consists of a Genetic Algorithm (GA) and a Cell Transmission Simulation (CTS) based Incremental Logit Assignment (ILA) procedure. GA is used to seek the upper level signal control variables. ILA is developed to find user optimal flow pattern at the lower level, and CTS is implemented to propagate traffic and collect real-time traffic information. The performance of the HSA is investigated in numerical applications in a sample network. These applications compare the efficiency and quality of the global optima achieved by Elitist GA and Micro GA. Furthermore, the impact of different frequencies of updating information and different population sizes of GA on system performance is analyzed.

Stochastic adaptive control model for traffic signal systems

Abstract: An adaptive control model of a network of signalized intersections is proposed based on a discrete-time, stationary, Markov decision process. The model incorporates probabilistic forecasts of individual vehicle actuations at downstream inductance loop detectors that are derived from a macroscopic link transfer function. The model is tested both on a typical isolated traffic intersection and a simple network comprised of five four-legged signalized intersections, and compared to full-actuated control. Analyses of simulation results using this approach show significant improvement over traditional full-actuated control, especially for the case of high volume, but not saturated, traffic demand.

Two-Level Integrated Optimization System for Planning of Emergency Evacuation

Abstract: This paper presents a two-level integrated optimization system for use in generating the candidate set of optimal evacuation plans that serve as the input for simulation-based evacuation systems. In the proposed system, the high-level optimization aims to maximize the throughput during the specified evacuation duration, and the low-level optimization is intended to minimize the total travel time as well as the waiting time for the entire operation if the specified duration is sufficient for meeting all evacuation demands. To effectively represent traffic flow relations with mathematical formulations, this paper employs the cell transmission concept, but with a revised formulation for large-scale network applications. The performance of the proposed models and their applicability has been tested with a microscopic simulation program that replicates the Ocean City evacuation network. Evaluation results from these numerical studies have demonstrated the promising properties of the proposed integrated optimization system.

Microsimulation models incorporating both demand and supply dynamics

Abstract: There has been rapid growth in interest in real-time transport strategies over the last decade, ranging from automated highway systems and responsive traffic signal control to incident management and driver information systems. The complexity of these strategies, in terms of the spatial and temporal interactions within the transport system, has led to a parallel growth in the application of traffic microsimulation models for the evaluation and design of such measures, as a remedy to the limitations faced by conventional static, macroscopic approaches. However, while this naturally addresses the immediate impacts of the measure, a difficulty that remains is the question of how the secondary impacts, specifically the effect on route and departure time choice of subsequent trips, may be handled in a consistent manner within a microsimulation framework. The paper describes a modelling approach to road network traffic, in which the emphasis is on the integrated microsimulation of individual trip-makers’ decisions and individual vehicle movements across the network. To achieve this it represents directly individual drivers’ choices and experiences as they evolve from day-to-day, combined with a detailed within-day traffic simulation model of the space–time trajectories of individual vehicles according to car-following and lane-changing rules and intersection regulations. It therefore models both day-to-day and within-day variability in both demand and supply conditions, and so, we believe, is particularly suited for the realistic modelling of real-time strategies such as those listed above. The full model specification is given, along with details of its algorithmic implementation. A number of representative numerical applications are presented, including: sensitivity studies of the impact of day-to-day variability; an application to the evaluation of alternative signal control policies; and the evaluation of the introduction of bus-only lanes in a sub-network of Leeds. Our experience demonstrates that this modelling framework is computationally feasible as a method for providing a fully internally consistent, microscopic, dynamic assignment, incorporating both within- and between-day demand and supply dynamics.

Application of Microscopic Simulation Model Calibration and Validation Procedure: Case Study of Coordinated Actuated Signal System

Abstract: In the application of microscopic simulation models, the importance of model calibration and validation cannot be overemphasized. A recent study proposed a systematic approach for conducting a simulation model calibration and validation procedure on the basis of experimental design and optimization and applied it to an isolated intersection with a VISSIM simulation model. The present study further evaluates the previously developed simulation model calibration and validation procedure by applying it to an urban arterial network consisting of 12 coordinated actuated signalized intersections. Both VISSIM and CORSIM simulation models were used. Travel time was used for the calibration measure, and maximum queue length was used for the validation measure. Study results showed that calibrated and validated simulation models were able to represent field conditions adequately, whereas default parameter-based models could not. As such, the previously developed simulation model calibration and validation procedure...

Transportation corridor decision-making with multi-attribute utility theory

Abstract: This paper provides a description of how decisions concerning transportation programmes and projects can be made in the context of sustainable transportation. It provides information on identifying appropriate performance measures for sustainable transportation and then quantifying these measures with a traffic simulation model (CORSIM) as well as transportation environmental models. The quantified performance measures were then used with three decision making methodologies. The test bed used for this study comprised a transportation corridor in Tshwane, South Africa and one in Houston, Texas. A method based on the multi-attribute utility theory (MAUT) techniques was found to be the best because a broad range of quantitative and qualitative sustainability issues can be included in the decision-making process. In addition, the disaggregate approach proposed in this paper made it possible for decisions to be made at the individual link level.

A discrete-event mesoscopic traffic simulation model for hybrid traffic simulation

Abstract: The paper presents a mesoscopic traffic simulation model, particularly suited for the development of integrated meso-micro traffic simulation models. The model combines a number of the recent advances in simulation modeling, such as discrete-event time resolution and combined queue-server and speed-density modeling, with a number of new features such as the ability to integrate with microscopic models to create hybrid traffic simulation. The ability to integrate with microscopic models extends the area of use to include evaluation of ITS systems, which often require the detailed modeling of vehicles in areas of interest, combined with a more general modeling of large surrounding areas to capture network effects of local phenomena. The paper discusses the structure of the model, presents a framework for integration with micro models, and illustrates its validity through a case study with a congested network north of Stockholm. It also compares its performance with a hybrid model applied to the same network

Microscopic simulation model calibration and validation handbook.

Abstract: Microscopic traffic simulation models are widely used in the transportation engineering field. Because of their cost-effectiveness, risk-free nature, and high-speed benefits, areas of use include transportation system design, traffic operations, and management alternatives evaluation. Despite their popularity and value, the credibility of simulation models falls short due to the use of default parameters without careful consideration. Improper model parameters prevent simulation models from accurately mimicking field conditions, limiting their ability to aid decision-making. Therefore, the user needs to pay more attention to fine-tune each model that they are using by calibrating the parameters inside the model. To summarize, we can define calibration as the adjustment of model parameters such that the model’s output more closely represents field conditions. The intention of this handbook is to outline and explain the calibration and validation procedure for the parameters controlling human and vehicle characteristics for CORSIM and VISSIM.

CoSIGN: A Parallel Algorithm for Coordinated Traffic Signal Control

Abstract: The problem of finding optimal coordinated signal timing plans for a large number of traffic signals is a challenging problem because of the exponential growth in the number of joint timing plans that need to be explored as the network size grows. In this paper, the game-theoretic paradigm of fictitious play to iteratively search for a coordinated signal timing plan is employed, which improves a system-wide performance criterion for a traffic network. The algorithm is robustly scalable to realistic-size networks modeled with high-fidelity simulations. Results of a case study for the city of Troy, MI, where there are 75 signalized intersections, are reported. Under normal traffic conditions, savings in average travel time of more than 20% are experienced against a static timing plan, and even against an aggressively tuned automatic-signal-retiming algorithm, savings of more than 10% are achieved. The efficiency of the algorithm stems from its parallel nature. With a thousand parallel CPUs available, the algorithm finds the plan above under 10 min, while a version of a hill-climbing algorithm makes virtually no progress in the same amount of wall-clock computational time

A platoon-based traffic signal timing algorithm for major-minor intersection types

Abstract: This paper presents a platoon-based traffic signal timing algorithm that reduces traffic delays at major–minor type of intersections. The algorithm reduces traffic delays at intersections by minimizing the interruptions to vehicle platoon movements on the major roads. In this paper, the characteristics of vehicle platoons are discussed, including the key platoon variables and their mathematical distributions. Then the platoon-based traffic signal timing algorithm is illustrated with proposed platoon detector placement and signal control logic. Further, through computer simulations it is shown that the platoon-based algorithm provides better performance at major–minor types of intersections than conventional signal timing algorithms.

Real-Time Traffic Simulation With a Microscopic Model

Abstract: This paper describes a microscopic model that is able to simulate traffic situations in an urban environment in real time for use in driving simulators. Two types of vehicles are considered in the simulation, namely the user-driven vehicle at the center of the simulation model and the other vehicles that interact with it and its surroundings, which configure the developed traffic model. Simulation is performed in a reduced zone, called the control zone, surrounding the user-driven vehicle. This control zone is a mobile zone centered on the user-driven vehicle. The size of the control zone depends on the maximum number of vehicles involved simultaneously, the traffic density, and the driver's limit of visibility. The other vehicles involved in the traffic simulation are created or destroyed within the limits of the control zone. The general behavior of the traffic model is based on the following theory. Vehicles have an associated driver model that establishes several control functions for them to follow the path, while the steering, acceleration, and braking maneuvers follow certain models of behavior. A traffic light regulation is also included but only in the control area. The possibility of introducing anomalous traffic situations into the simulation is also considered, such as the presence of obstacles, abnormal maneuvers, etc. The developed model is immediately applicable to large-scale driving simulators for driver training, traffic control studies, and safety studies

Estimation of Driver Reaction Time from Car-Following Data: Application in Evaluation of General Motor–Type Model

Abstract: Driver behavior plays an important role in modeling vehicle dynamics in a traffic simulation environment. To study one element of general driver behavior, that of car following, an advanced-instrumented vehicle has been applied in dynamic data collection in real-traffic flow on Swedish roads. This paper briefly introduces the car-following data collection and smoothing methods. Moreover, spectrum analysis methods based on Fourier analysis of car-following data are introduced to estimate driver reaction times, a crucial parameter of driver behavior. A generalized general motor-type model was calibrated, an extension of the classic nonlinear general motor model, in a stable following regime based on estimated driver reaction times. The calibrated model was then evaluated by closed-loop simulations.

Development of an Optimization Methodology for Adaptive Traffic Signal Control at Diamond Interchanges

Abstract: This research develops a methodology and a corresponding implementation algorithm to provide optimal signal control of diamond interchanges in response to real-time traffic fluctuations The problem is formulated as to find a phase sequencing decision with a phase duration that makes a prespecified performance measure minimized over a finite horizon that rolls forward The problem is solved by a forward dynamic programming (DP) method The optimal signal switches over each 25 s interval are found for each horizon of 10 s The optimization process is based on the advanced vehicle information obtained from loop detectors set back a certain distance from the stop line Vehicle trajectories from detections till future arrivals and departures is modeled at the microscopic level to estimate the traffic flows at the stop-line for each horizon The DP algorithm is coded in C++ language and dynamically linked to AIMSUN, a stochastic microsimulation package, for evaluation The simulation results have exhibited that the DP algorithm is superior to PASSER III and TRANSYT-7F in handling demand fluctuations for medium to high flow scenarios when the field demand is increased from the one used in off-line optimization The performance of the three algorithms is almost identical if the simulation demand is similar to off-line demand situation and does not vary much

Athens 2004 Olympic Games: Transportation Planning, Simulation and Traffic Management

Abstract: Even before the 2004 Olympic Games, Athens was a badly congested metropolitan area. This article describes how Athens planned and managed the transportation infrastructure to ensure that Olympic participants, spectators and workers could arrive and depart from their destinations with minimal delays. A systematic effort was needed to manage the addition of large and concentrated (in terms of both space and time) traffic generated by the Olympics. A strategic plan and operations plan were prepared to facilitate transportation management. Simulation models and prediction tools were used to estimate Olympic traffic movements. A large number of road and public transportation projects were completed to expand and improve the transportation infrastructure. Transportation was also facilitated through the use of dedicated lanes and restrictions in the use of private vehicles. The improved infrastructure and the systematic effort to manage traffic admirably served their purpose during the Olympics, and now provide Athens with the benefits of a non-congested road network and demand management experience. Athens can also serve as a model for future Olympic host cities.

Estimation of Traffic Dynamics Models with Machine-Learning Methods

Abstract: Speed-density relationships are a classic way of modeling stationary traffic relationships. Besides offering valuable insight into traffic stream flows, such relationships are widely used in dynamic traffic assignment (DTA) systems. In this research, an alternative paradigm for traffic dynamics models, appropriate for traffic simulation models and based on machine-learning approaches such as k-means clustering, k-nearest-neighborhood classification, and locally weighted regression is proposed. Although these models may not provide as much insight into traffic flow theory as speed-density relationships do, they allow for easy incorporation of additional information to speed estimation and hence may be more appropriate for use in DTA models, especially simulation-based models. This paper (with data from a network in Irvine, California) demonstrates that such machine-learning methods can considerably improve the accuracy of speed estimation.

Calibration of Vissim for Bus Rapid Transit Systems in Beijing Using GPS Data

Abstract: Bus Rapid Transit (BRT) systems have grown in popularity in recent years. With the rapid development of computer technologies, using microscopic simulation models to study various strategies on planning, implementation and operation of BRT systems has become a hot research area in the field of public transportation. To make the simulation models accurately replicate field traffic conditions, model calibration is crucial. This paper presents an approach for calibrating the microscopic traffic simulation model VISSIM using Global Positioning System (GPS) data for application to Beijing BRT systems. The Sum of Squared Error (SSE) of the collected versus simulated vehicle speeds at the cross-sections along the test route is specified as the evaluation index. A Genetic Algorithm is adopted as the optimization tool to minimize the SSE. Taking the Beijing North-South Central Axis BRT Corridor as a case study, it shows that the proposed approach is a practical and effective method for the model calibration.

Evaluation of Safety Effects of Driver Assistance Systems through Traffic Simulation

Abstract: Road safety is a major concern in all countries, and large efforts are constantly dedicated to create safer traffic environments. Today increasing attention is turned toward active safety improving countermeasures that improve road safety by reducing accident risks. Such active countermeasures include advanced driver assistance systems (ADAS). To ensure that these new applications result in real safety improvements, a priori estimations of safety effects are needed. This paper considers estimation of the safety effects of ADAS through traffic simulation. Requirements imposed on a traffic simulation model to be used for ADAS evaluation are presented, and a car-following model to be used in simulations that include ADAS-equipped vehicles is proposed. ADAS have an impact on traffic through the functionalities of ADAS and through changes in driver behavior for ADAS-equipped vehicles. Driver behavior for ADAS-equipped vehicles has usually not been considered in previous simulation studies, including those for ADAS-equipped vehicles. Simulation runs of rural road traffic that used the proposed car-following model did, however, indicate that behavioral changes caused by the ADAS were important factors for the safety impact. Modeling of the behavior of drivers in ADAS-equipped vehicles is therefore essential for reliable conclusions on the road safety effects of ADAS.

Stochastic Heuristic Dynamic Assignment Based on AIMSUN Microscopic Traffic Simulator

Abstract: The deployment of intelligent transportation systems must be assisted by suitable tools to conduct the feasibility studies required to test the designs and evaluate the expected impacts. Microscopic traffic simulation has proved to be the suitable methodological approach to achieve these goals. One of the most critical aspects of the dynamic simulation of road networks based on a microscopic approach—namely, how to perform a heuristic dynamic assignment, the implied route choice models, and whether under certain criteria the approach can achieve stochastic user equilibrium—is discussed.

An adaptive dissemination mechanism for inter-vehicle communication-based decentralized traffic information systems

Abstract: Inter-vehicle communications (IVC) has the potential to play an important role in many future vehicle and traffic applications. Much of this will occur in the automated vehicle control and safety systems (AVCSS) arena, and to a lesser extent in the advanced transportation management and information systems (ATMIS) arena. One such ATMIS application where IVC can be used is in decentralized traffic information systems. These systems do not require extensive infrastructure and management centers to collect and disseminate traffic information. Instead, information can be shared among vehicles through periodic broadcast messages. An adaptive dissemination mechanism for this is described in this paper. In the proposed design, each participating vehicle can adapt their transmission interval according to the current traffic speed and also disseminate the traffic information of different segments at different rates according to the distance to its current position. This dissemination scheme ensures the efficient distribution of information within the vehicle network. We have designed, developed, and tested this methodology using a unique traffic simulation environment that has been effectively augmented with wireless communication capability. Both analysis and simulation results show that the bandwidth that the system requires is far below the bandwidth of current 802.11 wireless links and the system can reach the accuracy requirement even at a low penetration rate

A packet-level characterization of network traffic

Abstract: In this paper we show results from a packet-level traffic characterization aiming at finding spatial and temporal invariances of TCP based applications, such as HTTP and SMTP. We developed a methodology and a software architecture to build packet-level statistical characterization of network traffic based on large traces captured from wide area networks. In order to show the efficacy of the proposed packet-level approach, we applied our methodology to the traffic generated by applications running over HTTP - a typology of traffic that has been extensively studied in literature even if, as far as we know, no accurate packet-level characterization has been proposed as yet with regard to it - and to SMTP traffic. We analyzed traffic from high-speed access links of two different networks and, contrary to common beliefs, the results show properties of spatial and temporal invariance. The study of SMTP has been proposed to demonstrate the generalization of a packet-level approach. Indeed, results prove the general applicability of the methodology and, at the same time, how - also at packet level - different traffic shows different characterizations. Characterization results can be used in platforms for traffic simulation (like ns or ssfnet) and traffic generation (like D-ITG or MGEM).

Set of New Traffic-Responsive Ramp-Metering Algorithms and Microscopic Simulation Results

Abstract: A novel switching traffic-responsive ramp-metering controller adapts to different traffic dynamics under different congestion conditions: free-flow or congested. The approach of multirate linear quadratic control with integral action is used to compensate for disturbances and to accommodate the difference between the model sampling time and the metering-rate update interval. In addition, a queue length regulator is designed to prevent the queue from exceeding the ramp storage capacity and yield improved performance over the current ad hoc queue override scheme. Subsequently, a queue length estimator is designed to provide feedback to the queue length regulator with the queue-detector speed data that are available in the field. A local ramp-metering control strategy is proposed to achieve the control goal of reducing the spatial and temporal span of the congestion, while satisfying the on-ramp storage capacity constraints, by using locally available information. Test results on a calibrated microscopic traffic simulator demonstrate the performance and effectiveness of the switching ramp-metering controller, the queue length estimator and regulator, and the overall control strategy. The total vehicle and passenger congestion delays are both reduced by 16%, and the total travel time is improved by 5.6%. As a comparison, simulation results of ALINEA are also presented.

Behavior-based consistency-seeking models as deployment alternatives to dynamic traffic assignment models

Abstract: This paper proposes a behavior-based consistency-seeking (BBCS) model as an alternative to the dynamic traffic assignment paradigm for the real-time control of traffic systems under information provision. The BBCS framework uses a hybrid probabilistic–possibilistic model to capture the day-to-day evolution and the within-day dynamics of individual driver behavior. It considers heterogeneous driver classes based on the broad behavioral characteristics of drivers elicited from surveys and past studies on driver behavior. Fuzzy logic and if–then rules are used to model the various driver behavior classes. The approach enables the modeling of information characteristics and driver response to be more consistent with the real-world. The day-to-day evolution of driver behavior characteristics is reflected by updating the appropriate model parameters based on the current day’s experience. The within-day behavioral dynamics are reactive and capture drivers’ actions vis-a-vis the ambient driving conditions by updating the weights associated with the relevant if–then rules. The BBCS model is deployed by updating the ambient driver behavior class fractions so as to ensure consistency with the real-time traffic sensor measurements. Simulation experiments are conducted to investigate the real-time applicability of the proposed framework to a real-world network. The results suggest that the approach can reasonably capture the within-day variations in driver behavior model parameters and class fractions in the traffic stream. Also, they indicate that deployment-capable information strategies can be used to influence system performance. From a computational standpoint, the approach is real-time deployable.

A composite traffic flow modeling approach for incident-responsive network traffic assignment

Abstract: This paper presents a hybrid traffic simulation-based model to address the network traffic route choice issue under conditions of lane-blocking incidents on surface streets. The proposed approach includes four sequential mechanisms: (1) link flow loading, (2) link traffic moving, (3) link cost calculation, and (4) searching the shortest path. To deal with the traffic flows moving on lane-blocking links, specific incident-induced link traffic flow models, which are extended from the Lighthill–Whitham (L–W for short) model, are formulated. A simulation-based approach is then proposed to determine the instantaneous shortest path associated with each vehicle approaching to each given intersection on the network. In addition, numerical examples associated with diverse incident scenarios are investigated. The numerical results demonstrate the competitiveness of the proposed simulation-based method by reducing the network-wide path travel time by 11.4% and the incident impact on link traffic flows by 66.7% in comparison with the Paramics traffic simulator. It is expected that this study can provide linkage between the fields of incident management and dynamic traffic assignment that will allow the development of such related technologies as real-time incident-responsive route guidance and incident management systems.